As software-as-a-service is becoming more viable for many companies, they search for accessibility, functionality, and versatility, a reason why the global business scenario took off with record revenues in the last decade or so. SaaS models appear to be a popular service-based approach with more cloud services integration.

2020 gave cloud usage momentum like never before. With more companies moving their on-premise businesses to the cloud, the demand for service-based software has shot up. SaaS still dominates the biggest market segments amongst cloud services and is expected to grow to USD 138.2 Bn in 2022.

SaaS will likely go through certain robust changes in the 2020s and coming decades. (SaaS BI) tools find acceptance in several new markets and streamline business models to maximize efficiency.

Enterprises worldwide are looking at new-age technology and tools to boost productivity, and SaaS is taking a new shape. Here we will look at the rising trends.

1. Artificial Intelligence

AI-driven automation will be a standard SaaS fixture with a predictable market value of USD 733.7 Bn by 2027. AI is set to drive ultra-responsiveness by automating repetitive tasks and optimizing human capabilities to drive greater product, service, or content personalization while gaining a deeper, data-driven understanding of the audience’s needs.

Modern software providers are using AI-run data alerts for pattern recognition and detection of anomalies, thus, enabling complete control over business processes. SaaS paired with AI capabilities can boost its core characteristics. It allows rapid customization through NLP to process voice control and speech patterns and has immense opportunities for customer service capabilities.

These capabilities also improve security parameters through quick identification and troubleshooting through in-built self-recovery and augment human capabilities by speeding up overall responsiveness through immediate forecasts.

2. Machine Learning

Machine Learning has empowered SaaS with automated onboarding and ultra-responsiveness with the help of AI-powered chatbots. It will also automate the onboarding process of new customers and customer service. The new wave of ML is focused on minimizing significant internal operations through innovations.

It can empower offerings to become self-improving and offer intelligence and operational efficiency to drive industries. The ML-based SaaS models will improve internal collaborations, analyze data and insights better, and train software solutions to learn from interactions for greater levels of intelligence and efficiency.

3. Vertical SaaS

While horizontal SaaS focuses on clients, vertical SaaS targets clients through customization within specific supply chains and industries. Innovations in vertical SaaS could enable enterprises to refine the options for customization through industry-specific and cost-effective solutions.

It seamlessly integrates industry-specific compliance for better transparency and ropes in a host of data governance procedures; the pre-determined KPIs and metrics in vertical SaaS provide analytics that businesses can utilize to access long-term projects.

4. White-Labeling

Startups are going to use white-labeling to gain market share economically. Since white labeling allows an enterprise to develop, test, and sell an optimized and finalized platform to another company, startups need not build solutions from scratch.

On the other hand, software companies selling white-labeled platforms can generate new RoI streams and market themselves as platform developers. They can focus on their value proposition, strategy, and branding.

5. Micro SaaS

In the decade of 2020s, the market may reach a thaw despite its brilliant numbers. The competition will likely give rise to micro SaaS businesses run by small teams to provide an extension of services to an existing platform to create an enhanced value for the SaaS product.

This market for miniature extension services will be specialized to an industry or userbase and is likely to operate without external funding.

6. API Connectors

The vast number of SaaS adoptions has left a gap between the need and competencies to handle the integration of these solutions into an existing business system. Not every business wants to move all their on-premise operations to the cloud.

Those who want to harmonize the SaaS solutions with their existing solutions need smart APIs that efficiently manage legacy systems and provide security against data breaches.

7. Centralized Analytics

Businesses are looking forward to data streaming processes for deeper customer insights. Data analytics is becoming an essential component in service-based software businesses, and data-driven decisions are emerging as a necessity for futuristic companies.

Centralized analytics may uncover hidden insights like performance dashboards. The SaaS models have an in-built centralized nature enabling data access from anywhere and making business processes transparent.

Experts say investment and value in analytics-centric SaaS models will rise by 23.3% by 2022. It will become a central component of almost every service-based software platform, making business intelligence and data-driven decisions powerful, and enabling users to discover hidden insights.

8. Low-code

‘Low-code’ structures have enabled startups to bring their SaaS solutions with minimal technical expertise. But it will not eliminate the need for developers or engineers. It will simplify the integration of aligned technology so that there is an investment to drive innovation.

• It can accelerate digital transformation and innovation.
• It can reduce an enterprise’s current IT or technical backlog and boost responsiveness.
• It can drive down the necessity for or dependency on hard-to-hire technical skills.
• It can protect the business against aggressive technological churn.
• It can improve internal processes.

Data-focused approaches drive the future of SaaS business solutions. These forward-thinking concepts are set to propel the industry to dizzying new heights. As enterprises integrate business intelligence and smart data to develop service-based solutions, more futuristic and practical cloud solutions will be developed.

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